The field of the invention relates generally to modeling techniques for estimating adoption of trends, and more specifically, to a system and method for predicting associated needs related to the use of electric vehicles.
Electric vehicles are relatively new to the marketplace. Many businesses and government agencies would like to forecast the use of these vehicles by specific locations. Unfortunately, there is little historic data that could be used for traditional mathematical modeling. One approach that can be used in the absence of data is to use models based on expert knowledge. This is especially important if there are many heterogeneous factors can affect the likelihood of consumers to adopt electric vehicles. Capturing expert knowledge in a form that can be used in software-based models has long been a challenge.
The roots of the approach can be found in medical diagnostics. This approach originally attempted to simulate the thought process of physicians that attempt to reason over several pieces of evidence to arrive at a diagnosis. This process uses a mathematical technique to “accumulate” evidence to evaluate a hypothesis. A particular approach described in U.S. Pat. No. 6,951,008, to the instant inventor, established the mathematical details of this approach but not the difficulty of formulating a model structure and of extracting knowledge from experts to calibrate the models.
At least some known agent-based models tend to use multiple types of agents which interact strongly with each other. There is an underlying assumption that all agents behave in a logical fashion and are driven by a limited set of factors, mostly financial. These models tend to be difficult for non-modeling experts to understand which tend to reduce the credibility of the output. Additionally, the purchasing decision for electric vehicles is not always highly logical but can be based on other subjective types of factors such as image enhancement.